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CHAPTER 1: INTRODUCTION

Growing number of wireless users and high data rate multimedia applications

with varying QoS requirements for 3G and beyond wireless systems, are demanding

novel communication techniques and network architectures. Researchers are investigating

various aspects of wireless systems to achieve this. This includes, but is not limited to

signal processing, interference mitigation techniques, smart antennas, medium access

control, wireless architectures, radio resource management, etc. The idea of exploring

new wireless architectures other than the traditional cellular network is quite interesting.

However, these new architectures will be appealing if they are flexible enough to

integrate with the existing universally deployed cellular networks.

Multi-hop (MH) network is one such architecture in which relays are used to

forward the traffic of the users having poor coverage to the base stations. The concept of

multi-hopping or relaying is not new [1,2,5], and it is the basis of ad-hoc networks having

an infrastructure- less architecture, i.e. no base stations or access points . However, the

consideration of multi-hopping in infrastructure-based architectures like cellular networks

has recently gained significant interest [1,5,17]. Traditionally, in cellular networks,

coverage enhancement can be achieved in the following two ways.

§ Installing more base stations in the network. Although this resolves the coverage

problem to a great extent but still cannot guarantee connectivity to nodes under

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deep shadowing or in small coverage gaps. Moreover, this solution is expensive

and may not be viable in low user density areas.

§ Installing repeaters in low coverage regions in the network such as subways,

tunnels, covered parking lots, etc [20,21]. Repeaters are inexpensive, but they

simply boost all the received signals without intelligence, resulting in unnecessary

high interference. In 2G wireless networks, built for voice communication only,

such repeaters work fine. However, for 3G systems and beyond with voice, data

and multimedia services with varying QoS requirements, such simple repeaters

are not adequate.

Conversely, relays are intelligent units, which forward the signals of only those

nodes that are in need of assistance (experiencing certain QoS degradation, such as

inadequate SINR). The relaying can be performed by either separate fixed entities

deployed at carefully selected locations in the network or by the user terminals

themselves. The later is also termed as peer-to-peer relaying. In case of separate network

entities, a relay’s functional complexity is less than that of BS but more than that of

ordinary node terminals. In peer-to-peer relaying, sometime also referred to as user

cooperative relaying, users with viable SINR links to the base stations, apart from their

own communication, support other users. The more the user density, the higher is the

probability of finding good relays. Hence, enhanced coverage comes from the user nodes

and not necessarily from the base stations as in traditional single-hop (SH) cellular

network.

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Another advantage of relaying is that it requires lower transmit power than that of

direct node-BS links in traditional cellular networks for the same SINR. This is because

multihop routes have short intermediate links to the destination, which leads to low path

loss and as a result smaller transmit power is required to achieve the desired signal

strength [10,11]. This results in reduced co-channel interference leading to increased

system capacity and enhanced battery life. However, there are some concerns and issues

associated with multi-hop communication such as complex routing and channel

assignment schemes, large control signaling overhead, high latency, increased battery

power consumption, sophisticated and thus costly user terminals, etc.

1.1 Thesis Motivation

Multihopping in traditional cellular network seems to be an interesting idea,

especially if peer-to-peer relaying is employed. Peer-to-peer relaying means that no

additional infrastructure is needed, and seamless integration with existing single-hop

networks can be easily implemented, although it implies some added complexity on user

terminals. It is attractive not only in terms of cost, but also for fast deployment time

(software modification) especially in areas where infrastructure expansion is difficult to

realize. Multihopping in peer-to-peer mobile cellular networks has shown significant

improvement in coverage by providing connectivity to nodes in deep shadowing, near the

edge or beyond the regular boundaries of a cell [4,12]. However, not enough research

literature is available to establish concrete understanding of multi-hopping system

performance. Moreover, some issues associated with mobility like handoff, Doppler’s

4

effect, fast channel estimation, adaptive routing, battery drain, etc., have raised concerns

and debates on the viability of peer-to-peer relaying in mobile networks.

To address these concerns, it would be natural to study multi-hopping in fixed

wireless network first, before considering it for mobile communication. Fixed wireless

multi-hop networks are also referred to as Wireless Mesh Networks, where every node is

connected to other node via a LOS or NLOS link and the network looks like a mesh.

Mesh connectivity leads to a network with high coverage, route diversity, adaptability to

changing environment, tolerance to link failures, and interference avoidance capability.

Effective utilization of resources and network load balancing is easy to realize. Some

investigation on mesh network in the LMDS band has shown high node throughput and

spectral efficiency [3]. However, restriction of line of sight (LOS) is a prime

implementation barrier. To assure this, extra relay units have to be installed, which in turn

increases both upfront infrastructure and running cost. Based on the high potential of

multi-hopping, mesh network provisioning is recommended by IEEE 802.16 committee

on fixed broadband wireless access in 2-11 GHz band, in which LOS requirement is not a

concern [8].

This thesis investigates and analyzes the performance of cellular mesh network in

the framework of IEEE 802.16, but its analysis and findings are not necessarily limited to

it. A cellular network in a start-up phase with low user density and poor coverage is

considered. Peer-to-peer relaying is used whenever necessary to achieve connectivity.

Multihop performance is evaluated in a high frequency reuse environment with no

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additional relaying channels. The performance of multihop network is compared with that

of traditional single-hop cellular network using similar parameters for fair comparison.

1.2 Thesis Objectives

The main objectives of this research are:

1) To investigate the performance gains achieved by enabling peer-to-peer

multihopping in TDMA based fixed cellular wireless network with poor single-hop

coverage. Performance measures considered are outage probability, node

throughput and spectral efficiency coverage.

2) To investigate the sensitivity of network performance measures outlined above to

the number of frequency channels available in the network.

3) To analyze the reasons of performance improvement and constraints in single and

multihop fixed cellular network.

4) To investigate the performance gains achieved by enabling peer-to-peer

multihopping in a hostile environment with high frequency reuse and no separate

relays and relaying channels.

5) To investigate and analyze the impact of increasing node offered load on the

performance of single and multihop fixed cellular networks.

6) To investigate and analyze the impact of using multihop only when necessary on

various performance measures of fixed cellular networks.

7) To investigate whether the multihop offered performance gain is bounded by relay

density or channel resources.

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8) To investigate the number of hops required to provide multihop connectivity when

using the reserved policy of using minimum number of hops route first.

9) To investigate the impact of “free matching time slots” requirement in a TDMA

based multihop network.

1.3 Relevant Literature

The potential of relaying to give performance improvements in ad-hoc network

has created a lot of interest to explore its performance in cellular networks. A good

overview of relaying in fixed and mobile cellular networks is available in [17], which

identifies interesting research areas. A mathematical characterization of multihop

wireless channel is presented in [13]. Analog and digital relaying is discussed. Analog

relaying means that the signal received by the relay is amplified without processing to the

intended destination. Hence both the signal and noise are amplified. Digital relaying

refers to the decoding and re-encoding of the signal at the relay.

Multihop channels without and with diversity, and their mathematical

characterization are discussed in [13, 14]. It was found that multihop with diversity

always outperforms the multihop without diversity. Another work on multihop diversity

is presented in [23]. Peer to peer relaying in HiperLAN/2 is considered to measure

throughput using multihop and multihop chase diversity. Improved throughputs were

achieved on both schemes, however, at the cost of increased energy requirements due to

relaying.

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An interesting study to measure coverage enhancement in mobile cellular network

through peer-to-peer relaying is discussed in [4,18]. Adjacent cell channels were used for

relaying, with and without power control. Relaying is found to give significant

improvement in coverage in both cases. However if the cell size is big, power control

may not help much. For small cell size, power control minimizes the co-channel

interference and further contributes to coverage enhancement.

Impact of relay selection policy on the capacity enhancement of mobile cellular

network is found in [19]. Random, semi-smart and smart relay selection schemes are

discussed. It was found that there does not exist much difference in performance gains

from each. Therefore the overheads and complex processing associated with semi-smart

and smart selection schemes do not justify, and a simple relay selection scheme can give

the similar gains.

The capability of relaying to aid in load balancing of a network is discussed in

[15]. It was found that relaying effectively diverts the traffic of a highly loaded cell to the

adjacent cells with less traffic. This not only improves the systems performance in

general but also ensures effective utilization of resources.

Spatial diversity using neighbour user terminals in mobile cellular networks, also

termed as user cooperative diversity is presented in [11,24]. The results show a

significant improvement in node throughput due to reduced outage. Such user

cooperative spatial diversity in mobile environment can cause battery drain and

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undesirable situation for the user, but the user mobility gives high spatial diversity

advantages, especially under deep shadowing.

1.4 Thesis Organization

Chapter 2 describes the system model of the network considered in this study.

Network architecture describes the cell type, frequency reuse and user nodes distribution.

Source node, relay and relayee are defined. Then, resource management policies are

discussed, and local and global resource allocation policies are defined. Antenna type and

large scale path loss model considered are shown. Routing search algorithm is presented

with an illustrating example. Slot assignment policy and issue of free matching slot is

then explained with example. Finally, probabilistic characterization of network traffic is

explained under the traffic model.

Chapter 3 presents a tabulation of various system parameters, their type and

simulation values considered in this study. Simulation procedure is then briefly discussed

followed by flow charts of the main simulation and call admission procedure.

Chapter 4 discusses the simulation results. Simulation results are categorized into

three main sections: outage probability, node throughput and spectral efficiency

coverage. Graphical results are presented along with detailed analysis of both single-hop

and multihop results with respect to the number of frequency channels for each

performance measure.

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Chapter 5 provides a brief summary of the thesis and concluding remarks. The

contributions of the thesis are highlighted. Later, a series of interesting future research

topics are identified.

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CHAPTER 2: SYSTEM MODEL

This chapter describes the system model used in the study. The entire system

model is broadly classified into network architecture, propagation, routing, and traffic

models. The network architecture model describes the network type, entities and resource

management policy. The propagation model explains the path loss model, link types and

related assumptions. The routing model describes the procedure used to develop the

routing table, route selection policy, followed by the channel assignment procedure. The

traffic model explains network traffic considered, and how burst arrival and size are

probabilistically modeled.

2.1 Network Architecture

The network scenario considered in this study is shown in Figure 2.1. A cellular

network is partitioned into four, square shaped cells with base station (BS) in the center

of the cell and user nodes uniformly distributed throughout the network. Square shaped

cells are considered for the purpose of simulation simplicity. A low node density, noise

limited network representing a start up phase is considered. The network has poor single-

hop coverage, mostly experienced by nodes at the edge of the cells or under deep

shadowing. Most of the studies on multihop (MH) networks consider more than two

network entities [3,5] such as base station, user node, access point, seed node, mesh

insertion point, wireless router, etc. However, this study considers only two main entities

typical of any cellular network, i.e. base station and user node. A normal user terminal

acts as relay for other nodes, i.e. there are no separate relay entities in the network; hence

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no additional infrastructure is needed. This is also termed as peer-to-peer relaying. This

leads to easy implementation and integration of multi-hopping feature through software

algorithms and routing protocols. It will also ensure a fair comparison with a single-hop

network (traditional cellular). The terminologies for network entities that will be used

hereafter are defined as follows:

§ Source Node: The user node at which the data transmission is initiated.

§ Relayee Node: The user node in need of relaying assistance. It could be a source

node or an intermediate relay node.

§ Relay Node: The user node, which apart from its own communication, is

assisting other node(s) to forward traffic to the base station (as in 2-hop link), or to

another relay node in the network (as in 3-hop link).

§ Base Station: The base station is primarily responsible for connecting nodes to

the backbone, along with managing most cont rol activities such as call admission,

route and channel assignment, radio resource management, scheduling, power

control, etc.

Single carrier channels are considered, while the employed multiple access

technique is synchronous TDMA. Synchronous means tha t all node transmissions on the

uplink are concurrent and slot synchronized. These transmissions could be from a node to

another node or from a node to a base station. A node requesting service is assigned a

unique frequency and time slot pair, and full channel bandwidth during the entire

duration of the slot.

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Figure 2.1. Cellular network under consideration, with user nodes

uniformly distributed

User Nodes

Base Station

x

x

Node at the edge of the cell with high path loss

Poor link due to

strong shadowing

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Aggressive frequency reuse is considered, with all carriers used in all cells. This

means no cell planning required and worst-case co-channel interference scenario

considered. No separate relaying channels are used, i.e. same frequency channels are used

for relaying as for regular single-hop communication with orthogonal time slots on two

consecutive hops of a particular link. This will ensure a fair spectral comparison of

cellular mesh network with traditional single-hop cellular network.

Network performance on the uplink or reverse link is analyzed. This is because,

with expected broadband applications such as video conferencing, telemedicine and

interactive remote training sessions, the uplink transmission will also require high data

rates like downlinks and will meet quality of services (QoS) requirements. Moreover

uplink performance analysis is considered relatively more complex than downlink,

because of the distributed nature of traffic generation, multiple concurrent transmission

and highly variable interference levels. Hence a proper study of the uplink will give

deeper understanding of the impact of enabling multi-hopping on network performance,

and will be equally applicable to the downlink.

2.2 Resource Management Scheme

The resource management scheme is used to manage and assign the spectral

resources (channels or time slots), the transmitted power , the admission of new calls and

access to the base stations. Since fixed transmit power is considered in this study,

resource management here refers only to how the channel (time slots) are managed and

allocated.

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2.2.1 Local Resource Management

Local resource management means that a user node in a particular cell can only be

serviced through its own (local) base station resources, and can only take relaying

assistance from nodes in that cell only. This approach is simple to implement, process

and manage, but may lead to non-optimum utilization of spectral resources (frequency

channels). This is especially true in case of non-uniform distribution of nodes or

unbalanced traffic in different regions of the network. Also, nodes at the edge of the cell

may experience high outage due to poor link quality and unavailability of relay nodes in

the same cell. Figure 2.2 illustrates a cellular mesh network with local resource

management scenario. The solid line represents a viable direct link from node to the base

station and the dotted line shows a viable node-to-node link. A link is considered viable

based on certain criterion. This criterion could be a threshold value of path loss or signal

to interference plus noise ratio, beyond which signal quality is unacceptable.

2.2.2 Global Resource Management

It means that a user node in a particular cell can be serviced through any base

station in the network, and can take relaying assistance from any node in any cell. This

approach is complex in terms of control information processing, implementation and

management, but may lead to optimum utilization of spectral resources (frequency

channels). This is also termed as resource pooling. With this type of resource allocation

policy, nodes with coverage problem have much more opportunities to get a good single-

hop or multihop link to one of the base stations, as shown in Figure 2.3.

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Figure 2.2. Connectivity in cellular mesh network with local resource

allocation policy

User Nodes Base Station (BS) Good Node-BS Link Good Node-Node Link

16

Figure 2.3 Connectivity in cellular mesh network with global resource

allocation policy

User Nodes Base Station Good Node-BS Link Good Node-Node Link

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In this study, global resource management policy is used, because we are

considering a low node density network (hence low relay density) with poor single-hop

coverage. Therefore, it is expected that many nodes will need relaying assistance.

Multihopping will increase as traffic grows, not only because of more demand of

resources (channels or time slots) from nodes not having initial single-hop coverage but

also from nodes initially having good single-hop coverage but their SINR had degraded

due to high frequency reuse in the network.

2.3 Antennas

Transmit and receive antennas at the user nodes and base stations are directional,

switched beam type. The user end antennas are roof mounted. Since the user nodes are

fixed, the location of each user is exactly known; hence with the use of switched beam, a

node can exactly point its antenna beam towards the intended receiver or transmitter. In

modeling, the main lobe gain is fixed throughout the antenna beam width. Similarly, the

side and back lobes have identical gain.

2.4 Propagation Model

This study considers a suburban environment like a moderately dense residential

area. The average signal power received at the base station or relay node can be

represented by the following formula [6]

PLGGP

P rttr = (2.1)

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where

Pt = Transmit power

Gt = Transmit antenna gain

Gr = Receive antenna gain

PL = Path loss

If the transmit power, antenna gains and path loss are given in dB scale, then the

average received power in dB can be represented as follows

Pr(dB) = Pt(dB)+Gt(dB)+Gr(dB)-PL(dB) (2.2)

The large scale path loss (PL) considered in this study is based on the following

log distance path loss model [6]

( ) σλπ

Xdd

nd

dBPLo

o +

+

= log10

4log20 (2.3)

where

PL = Path loss

do = Reference distance

n = Propagation exponent for path loss

λ = Wave length of frequency carrier

d = Distance between two nodes or node and base station

Xσ = Log normal shadowing with standard deviation of σ

The communication links are divided into two categories, a) node to node link and

b) node to base station links. Since on node to node links, both transmitter and receiver

antenna heights are low (although rooftop mounted), relatively higher path loss exponent

is considered, compared to node to base station link. Independent and fixed lognormal

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shadowing is considered on each link with zero mean and different values of standard

deviation for node-to-node links and node to BS links (relatively larger values for node to

node link, for the same reason mentioned above).

Multipath fading is not considered in this study assuming that it is taken care of

by micro diversity or some other means. It is expected, however, that due to the fixed

position of the user nodes, the fading would be slow and temporally correlated [22].

Since the frequency channels are considered around 2.5 GHz., therefore communication

is possible through both line of sight (LOS) and non line of sight (NLOS) links.

2.5 Noise Power

Additive white gaussian noise is considered. The noise power is calculated at the

receiver using the following relationship [9]

Pn = kToBcFn (2.4)

where,

k = Boltzman's constant 1.38x10-23 Joules/Kelvin.

To = System temperature, 300oK

Bc = Channel bandwidth

Fn = Thermal noise figure, 5 dB

2.6 Routing

For a source node to reach a base station using multi-hopping, it needs some

specific route. Usually, there is more than one acceptable multi-hop route for any node

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base station pair. The criterion for link acceptance could be a certain path loss or SINR

threshold value on all hops and/or a certain constraint on the maximum number of hops.

Once the criterion is chosen then an iterative search using some appropriate routing

algorithm can be applied to find the optimum route for transmission.

In this study, path loss is chosen as the cost function, rather than SINR since all

user nodes are fixed and as a result the large scale path loss (log distance path loss +

shadowing) is fixed on all links. Thus, we can develop a static multi-hop routing table for

each node-BS pair. Routing tables need not to be updated frequently, and are modified

only when new nodes join the network. In contrast to path loss, SINR is highly dynamic

and varies from slot to slot, thus we will have to resort to on-the-spot iterative search if

we use it as the cost for route selection. Pre-built routing tables can save lot of processing

time required for on-the-spot iterative search for optimum available route. Moreover, we

are doing burst level simulation, i.e. every new burst arrival at a certain source node may

be assigned a different route based on the availability; therefore at high traffic loads, such

on-the-spot iterative route search may not be an efficient solution and may lead to

undesirable delays and large buffering.

Furthermore, with routing table, “route diversity” is always available at hand.

Usually route diversity means that multiple routes are used to transmit copy of the same

message, and combine them at the final destination using maximal ratio combining or

some other method. In this study we did not use route diversity in this sense, but from the

perspective that a routing table at hand itself gives readily available route diversity to

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choose from. In other words a survivable network is present, where failure of one route

does not break the communication, and many alternates routes are available to keep the

communication active.

A question arises at this point: why opt for an exhaustive search algorithm rather

than any widely used fast converging algorithms such as Dijkastra’s or Bellman-Ford to

construct routing tables?. Actually during the course of our investigation, before choosing

the exhaustive search procedure, we did try to modify the classical Bellman Ford

algorithm to provide multiple 2-hop and 3-hop routes based on our criterion of

min{max(PLi)}. It was found that, although these algorithms are efficient in providing the

best route, they turned out to be not less complex than the exhaustive search when used to

calculate multiple m-hop routes. However, more investigation can be done in this area,

and if some solution already exists in the literature, it can be tested to compare the

efficiency.

2.6.1 Algorithm for Route Table Construction

A simple search algorithm is used to develop the routing tables. Only 2 hop and 3

hop routing tables are developed for each node base station pair. The algorithm uses

iterative sorting technique to arrange the routes, hence simple but exhaustive. The

maximum path loss value beyond which a link is not considered for communication is

termed as “path loss threshold” (PLth). The criterion used in this study, for setting up

(ordering) the multiple MH routes for any node-BS pair is:

Rs= min arg {max (PLi)} (2.5) for ∀ a∈A

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where,

Rs = m-hop routing table (sorted)

PLi = Path loss on the ith hop, i= 1,2 for 2-hop route, i=1,2,3 for 3-hop route

A = Set of all possible m-hop routes

The routing table algorithm is summarized as below:

Step 1: Reject all node to node and node to base station links with PL>PLth

Step 2: List all 2-hop and 3-hop routes between source node and base stations.

Step 3: Arrange in ascending order, the routes found in Step 2 using the criterion

min{max(PLi )}, where i=1,2 for 2-hop routes, and i=1,2,3 for 3-hop routes.

Step 4: If there is tie in max(PLi) value on multiple routes, then arrange those routes in

ascending order of min{Σ PLi }.

2.6.2 Example of Routes Search Algorithm

To clarify exactly how the routing algorithm works, consider the mesh network

illustrated in Figure 2.4. Consider the threshold path loss value (PLth) to be 120 dB. Let’s

say we are interested in finding the multiple routes from node#1 to the base station. As

shown, the direct link from the node#1 to the base station is unusable because of high

path loss. Next, the four steps algorithm is used to find all possible 2-hop and 3-hop

routes from node#1 to the base station. According to Step 1, all links having path loss

greater than 120 dB are discarded. Now, for 2-hop routes search, the step#2 is to list all

possible two hop routes from node#1 to the base station, and identify the highest path loss

link on each of those routes, as shown next.

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Figure 2.4 Example of mesh network considered for calculating

the route tables

85dB

PLth = 120dB 2

65dB 112dB

73dB 130dB

60dB

135dB

115dB

82dB

95dB 4

3

1

BS

Node

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In step#3, the 2-hop routes are arranged in the order of min{max(PLi )}, followed

by step#4, which is not applicable in this case. The final 2-hop route table for node#1 is:

Similarly, the outcomes of step#2 to step#4 for 3-hop routes are shown below

Step #2: Step #3:

2-Hop Route Link Path loss (dB)

1 - 2 - BS 85 65 1 - 4 - BS 73 95

2-Hop Route Link Path loss (dB)

1 - 2 - BS 85 65 1 - 4 - BS 73 95

3-Hops Routes Link Path loss (dB)

1 - 2 - 3 -BS 85 112 115

1 - 2 - 4 -BS 85 60 95

1 - 4 - 2 -BS 73 60 65

1 - 4 - 3 -BS 73 82 115

3-Hops Routes Link Path loss (dB)

1 - 4 - 2 -BS 73 60 65

1 - 2 - 4 -BS 85 60 95

1 - 2 - 3 -BS 85 112 115

1 - 4 - 3 -BS 73 82 115

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Step #4: 2.7 Route Selection Policy

Since high frequency reuse and fixed transmit power is considered; enabling

aggressive multihopping in this scenario might lead to high co-channel interference.

Based on this understanding, the used route selection policy is “minimum number of hops

route first”. This means, first the source node looks for a single-hop connection to a base

station with “matching” free slot and the achieved signal to interference plus noise ratio

(SINRach) greater than or equal to the SINRth value. If a good single-hop connection is

found, multihop routes are not evaluated, otherwise the source node explores all 2-hop

routes in the routing table, followed by 3-hop routes; if even a 3-hop route is not found,

the burst is denied service and outage occurs. If matching free slots are found on a

particular route, these free slots are checked for the required SINRth, if the received signal

to interference plus noise ratio SINRr< SINRth on any one link, this route is rejected and

the next best route in the table is explored. Figure 2.5 shows an example of route

selection using this policy. The SINRth considered is 4.5 dB. As illustrated, node 1 found

two good SINR matching free slots on the base stations. Hence the node is assigned the

best SINR route of 8.4 dB, although the source node has significantly higher SINR on the

3-Hops Routes Link Path loss (dB) 1 - 4 - 2 - BS 73 60 65

1 - 2 - 4 - BS 85 60 95

1 - 4 - 3 - BS 73 82 115

1 - 2 - 3 - BS 85 112 115

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2-hop and 3-hop routes. Some of the salient features of the minimum number of hops

route first assignment policy are as follow:

§ Less time slots used, meaning low hard blocking and outage.

§ Links with at- least SINRth used. This simply means that the primary objective of

this route selection scheme is to minimize the outage not to maximize the

throughput.

§ Algorithm simplicity.

2.8 Slot Assignment Policy

Whenever a node generates a data burst, it requests a time slot allocation from the

base station(s). The base station(s) measures the received signal to interference and noise

ratio (SINRr) on its free time slots of all channels with respect to the source node.

Consider a node i transmitting towards base station j on channel f during time slot s, then

the signal to interference plus noise ratio achieved by node i at BS j represented by

SINRi,jf,s would be,

∑

≠=

+

= sfK

ikk

sfkkjn

sfiijsf

ji

PGP

PGSINR ,

1

,

,,

, (2.6)

where

Gij = Path gain on the link between node i and base station j, this path gain includes the

effect of transmit and receive antenna gains also.

Pif,s = Transmit power of node i on slot s of channel f.

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Figure 2.5 Example of minimum number of hops route first policy

10.8 dB 24.7dB 18.3dB

11.6 dB 9.1 dB

5.7 dB

8.4 dB

14.1 dB 12.3 dB 16.6 dB

7.6 dB 13.8 dB

⇒ Selected

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Pn = Noise power

Kf,s = Total number of other nodes transmitting on channel f during time slot s

Pkf,s = Transmit power of node k on slot s of channel f

If SINRr on free slot(s) is greater than SINRth , then a suitable route (SH or MH) is

assigned to the source node for that particular burst session. Once a route is chosen, the

free slot with best SINR is allocated on each hop.

2.8.1 Issue of Free Matching Time slots

An associated constraint introduced by multi-hopping in TDMA based system

found during modeling is the need of “matching” free time slots rather than just free time

slots for any connection. In traditional single-hop TDMA, a node gets connected to the

base station on any free time slot, provided it has the required SINR, while in multi-

hopping, this constraint is due to the reservation of time slots on relay node by a relayee

node. It is even worse when frequency channels are few and/or there are few good relays

to the base station, and all nodes with poor coverage are trying to access the base station

through one of those few relays. This might lead to the rejection of many good possible

connections and can even lead to burst blockage.

The issue of matching free slot is illustrated through an example shown in Figure

2.6. As can be ascertained, node 4 has a good link to the base station(s), hence most of its

slots are already occupied by other nodes to forward their traffic. The occupied and free

slots shown in Figure 2.6 represent the current status on of the frequency channel. Now at

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Figure 2.6 Example of free matching time slot issue

1 2 3 4 5 6 7 8 9 10

1 2 3 4 5 6 7 8 9 10

1

4

1 2 3 4 5 6 7 8 9 10

BS

Hop 1

Hop 2

Occupied slot Free slot

Channel

30

this point node 1 wants the support of node 4 to relay its traffic. As illustrated in Figure

2.6 and Table 2.1, there are free matching slots available on first hop between node 1 and

node 4. However, on the second hop although the base station has free slots available, no

matching free slots found between node 4 and base station. Hence node 1 request cannot

be served and the call is blocked. A good resource management and scheduling scheme

can overcome this problem to a large extent (although there are associated overheads),

but its not accounted for in the system model for the sake of simplicity. Moreover, this is

only a concern found during the system modeling phase, but its seriousness is not yet

clear and need to be evaluated from the simulation results. Therefore in the simulation

modeling, statistics regarding this issue is collected to see its impact on outage.

Table 2.1 Results of example on free matching time slot issue

1st Hop 2nd Hop

Node1 Node4 Node4 BS

Free Time slots 1,3,4,5,6,7,9,

10

3,5,9,10 3,5,9,10 1,4,8

Matching free slots

3,5,9,10 Nil

Rearrange slots in SINR descending order

9,5,3,10 Nil

Select the first slot (best SINR slot) for this hop

9 Not Possible

31

2.9 Transmit Power and Modulation

The model considers fixed transmit power on all active links. This includes both

node to node and node to base station links. Although this lead to higher co-channel

interference levels, we exploited high Pt and good SINR links using adaptive modulation

and coding to achieve high node throughput. Different combinations of coded QPSK and

M-QAM are used. If any link on a route has SINRach< SINRth, then that frame will be

dropped. Adaptive coding and modulation (ACM) is selected independently on each hop

of the route based on the SINR level. Mapping of adaptive coding and modulation with

respect to SINR is shown in Table 2.2*, and is based on Bit Interleaved Coded

Modulation (BICM) [7], for BER=10-6.

SINR(dB) bps/Hz Adaptive coding and modulation

> 26.0 6 1 - 64 QAM

21.94-26.0 5.25 7/8 - 64 QAM

19.0-21.94 4.5 ¾ - 64 QAM

17.7-19.0 4 2/3 - 64 QAM

15.0-17.7 3.5 7/8 - 16 QAM

14.02-15.0 3 ¾ - 16 QAM

12.0-14.02 2.67 2/3 - 16 QAM

10.93-12.0 2 ½ - 16 QAM

7.45-10.93 1.5 ¾ - QPSK

4.65-7.45 1 ½ - QPSK

< 4.65 0 -

Table 2.2 Mapping of adaptive coding and modulation to SINR

* This mapping is derived from the data provided by Dr. Sirikiat Ariyavisitakul by private communication.

32

2.10 Buffered Data Transmission

Buffered transmission on each link is considered. It is assumed that every node

has enough buffer memory to accommodate its own data and that of its relayees.

Although buffered data transmission has some associated issues of introducing more

delay and hardware cost, it offers more benefit such as:

§ Flexibility of independently choosing adaptive coding and modulation levels on each

hop based on its SINR.

§ Simple call admission control policy.

§ Support of regenerative relaying.

§ Effective utilization of available resources: time slots are released as the data transfer

completes on a link, and are not occupied until the data is transferred from the source

to destination as in the case of no buffered data transmission.

Each source node generates a data burst of certain size (kbits) based on the traffic

model discussed in the next section. Once a route (SH or MH) is selected to serve this

burst, each transmitter (source node and relays) on this route will transfer data by

independently choosing a modulation and coding level based on the SINR on that

particular hop. Transmission on each hop l continues until the whole data burst is

transferred from the source to destination. Adaptive coding and modulation on each hop

can differ from frame to frame due to change in interference levels. Track of all active

burst sessions along with the size of data transmission in each hop are updated at the end

of every frame. A fair allocation of time slot resources is done, by assigning one slot per

33

frame to each hop of a route for a particular active burst session. This way more

concurrent active sessions can be set up, which will be required at high traffic levels.

Buffered transmission allows simple call admission policy. Any new call,

satisfying minimum of SINRth on all hops of a particular route is admitted. Contrary to

this, no-buffered data transmission requires connection oriented service, therefore same

SINR on all hops of a particular route has to be maintained to ensure smooth data

transfer. The same is true about all currently active sessions. This can be done in two

ways

§ Implement a strict call admission policy, such that all those calls (or queued) whose

admission may lead to degradation of SINR on any hop of all active routes are

denied service.

§ Use power control to maintain same SINR on the entire route, and this has to be

ensured for all active sessions.

Furthermore, the use of digital relaying as considered in this study, requires

buffering anyway, because received data has to be decoded, demodulated and re-encoded

before transmission on the next hop. Hence, the use of buffered transmission naturally

supports digital relaying.

Figure 2.7 illustrates an example of buffered data transferring on a 2-hop route.

The time scale T1, T2, T3,… represents the start time of each frame. Adaptive

modulation and coding on each hop is shown in the form of corresponding spectral

34

Figure 2.7 Example of buffered data transmission considered in the system model.

1.5 4

50K

4

30K 20K

1.5 3

15K 7.5K 27.5K

2 4

0 32.5K 17.5K

4

0 12.5K 37.5K

3

0 0 50K

T1

T2

T3

T4

T5

T6

Spectral Efficiency (info. bps/Hz)

35

efficiency (information bits per second per hertz). Each hop is assigned one slot for

transmission and it can accommodate 5000 symbols. A data burst of size 50 kbits is

initiated from a node at time T1, and data is transferred on each hop frame by frame

based on the spectral efficiency during the corresponding frame. As shown in Figure 2.7,

the minimum SINR (in terms of spectral efficiency) on the route is the bottleneck in data

throughput.

However, as each node complete its data transfer, it releases the resource (time

slot) so that it can help other nodes needing relaying assistant. This is particularly

important when good relays are few. The data transfer activity continues until the whole

burst reached the base station.

2.11 Traffic Model

The user nodes are considered to be generating bursty traffic sessions, typical of

http, ftp and some audio and video download applications. Single quality of service (non

delay sensitive, same SINRth) is considered for all bursts. The overall network traffic

arrival follows a Poisson distribution with a mean arrival rate of λ burst per second. Burst

size is exponentially distributed with a mean of µ kbits. Figure 2.8 illustrates how the

burst arrivals are served. T1, T2, … represent the time units in multiple of frame duration

(Tf). Burst requests B1, B2 and B3 arrived during frame time T1 get serviced at the start of

next frame time T2 if, successfully admitted. The service duration of a burst depends

upon the size and SINR on the route.

36

Figure 2.8 Illustration of burst arrival and start of service

B4

B5

B3

B2

B1

B1 B2 B3 B4 B5

T1 T2 T3 T4 T5 T6 0 Time

37

CHAPTER 3: SIMULATION DESCRIPTION

This chapter describes the system simulation developed to analyze the

performance of the mesh network discussed in the previous chapter. Section 3.1 includes

a list of all system parameters, their types and chosen values used in this simulation.

Section 3.2 highlights the major assumptions made in this simulation along with the

reasoning and limitations of each. Finally, Section 3.3 briefly describes the simulation

process and algorithms.

3.1 Simulation Parameters

System Parameter Type

Simulation Value

Network Architecture

Cellular - 4 square shaped cell, each 3x3 km2. - 200 nodes uniformly distributed in the network.

Network Entities

Node & Base Station

Carrier Frequency Around 2.5 GHz.

Channels

No. of Channels = 2-6, with 5 MHz. each

Frequency reuse factor

No frequency planning 1

Noise Power AWGN Noise Power = -130 dBW ( based on noise figure = 5 dB, & transmission bandwidth of 5 MHz)

Multiple Access

Synchronous TDMA All node transmissions are slot synchronized

Link Analysis Uplink or Reverse Link

Transmit Power

Fixed Pt = 2 watts

Path loss - Exponential path loss Node-BS links

38

plus independent and fixed shadowing.

- Reference distance do = 10m - Propagation exponent n = 3.8 - Zero mean lognormal shadowing with σ = 4 dB Node-Node links - Reference distance do = 10m - Propagation Exponent n = 4 - Zero mean lognormal shadowing with σ = 6 dB

Antenna Type - Roof top mounted -Directional switched beam at both BSs and nodes

- 30o beam width - Main lobe gain = 7 dB - Side & back lobe gain = 0 dB

Relaying Channel No separate relaying channels.

Zero

Maximum Permissible hops

3

Call Admission Policy

SINRach≥SINRth on all hops.

SINRth = 4.65 dB

Max. Acceptable Path loss for Multihopping.

Propagation path loss + shadowing

PLmax = 126 dB

Node Buffer Size Unlimited

Traffic Model Bursty - Burst arrival rate: Poisson distributed with mean λ=400-8400 burst/sec - Burst Size: Exponentially distributed with mean µ=15kbits.

Connection Type Semi Connection Oriented

1 slot per frame on each hop is assigned on the complete connection.

Frame Specs Fixed time slot duration

Frame duration=10ms No. of slots per frame=10

Service Types One - No of slot needed = 1 - SINRth = 4.65 dB - No delay constraint

Adaptive coding and modulation

Code rate & Modulation level mapped to SINR

Refer to Table 2.1 (Chapter 2)

Frame Error SINRach<SINRth on any hop.

SINRth = 4.65 dB

Automatic Repeat Request (ARQ)

Continuous ARQ - Upper limit on consecutive frame dropping before ARQ = 2 - Retransmit entire burst

39

3.2 Simulation Assumptions

§ Snap shot processing at frame level: This means that call admission and release

procedures, resource allocation decisions, SINR calculation, and statistics

collection are carried out at the start of each frame only. Nothing is changing in

between the frames.

§ Frame transmissions are slot synchronized: This is applicable to frame

transmissions from nodes (source node or relays(s)) to nodes as well as from

nodes (or relay) to base stations. This assumption is necessary to make sure that

co-channel interference and SINR are calculated properly. This is important for

slot assignment decision and for right selection of the coding rate and modulation

level.

§ Independent & fixed shadowing on all links : Since node density is low, it is

reasonable to assume that there is no spatial correlation between shadowing

values at different nodes, on both node-node and node-BS links. Also, fixed

shadowing is assumed based on the stationary nodes assumption.

§ Negligible Doppler’s shift: This assumption is valid due to stationary nodes.

§ Micro-diversity is tackling multipath fading: Temporally correlated multipath

fading is expected on each link, due to stationary nodes. However, multipath

40

fading is not considered in the simulation. It is assumed to be taken care of by

micro diversity or some other means, both on the nodes and base stations.

§ Unlimited buffer capacity on each node: This is assumed for modeling and

simulation simplicity. In addition, memory chips are pretty cheap to support this

assumption.

§ All nodes are active: This means that each node is generating the average node

traffic under consideration. Moreover, the nodes have to be in always on

condition irrespective of whether they are sending the data or not. This is to make

sure that a node is available to serve as relay whenever needed. No power

constraint is involved because of the fixed position of the node.

§ Separate control channels are available: This is necessary to share information

among nodes and between nodes & base stations (like ARQ acknowledgement,

slot assignment/release information, adaptive coding and modulation level to be

selected for the next transmission, start and end of the data transmission, etc.).

§ Continuous ARQ: It means that a receiver (node or BS) sends the

acknowledgement to the transmitter for every frame. This acknowledgment shows

whether the frame was received in error or not.

41

3.3 Simulation Algorithm and Flowcharts

A network level simulation was carried out to measure the performance of both

single-hop and multihop fixed cellular network. This is a hybrid, time and event driven

simulation. It is time driven in the sense that the simulation itself runs for a specified time

in terms of multiple of frame duration. It is event driven in the sense that changes in the

system (interference level, slot availability, etc.) and statistics collection depend upon the

burst arrival & departure events. The burst arrival events are generated before the start of

the simulation and are known a priori on the time scale. The burst departure event time is,

however, unknown a priori, because it depends on various random variables such as burst

size, node selection, node locations, SINR values, coding rate and modulation level, etc.

Routing tables from each node-BS(s) pair are developed before the start of the

main simulation, and are called as needed. Due to the use of switched beam directional

antennas, the interference experienced by nodes and base stations will depend on the

directivity of each transmitter (source node or relay). Since nodes are stationary, it is

possible to calculate accurately the receive antenna gains that each node and BS will

experience, with respect to a specific transmitter receiver pair. Therefore, receive

interference gain matrices are calculated prior to the start of the main simulation.

The entire simulation is conducted in the form of frame transmissions. Therefore,

the simulation time scale is in multiples of frame time. All call arrivals in the network

during the current frame transmission are processed and inducted at the start of the next

frame. On the other hand, all call departures during the current frame are processed and

42

resources released at the end of the current frame, before admitting new arrivals. Existing

calls requiring re-routing due to high frame outage are processed before admitting new

calls to ensure the connectivity of existing active calls. New call arrivals are assigned to

source nodes using uniform distribution, while burst sizes corresponding to those calls are

generated using exponential distribution. All these calls go through call admission

procedure where their SINRach are calculated. Those calls fulfilling the requirements of

having SINRach greater than SINRth, and subject to the availability of channel resources

(time slots) are assigned minimum number of hop route. Otherwise, the call will be

blocked and will contribute to outage.

The data transfer on each established call continues on a frame to frame basis

until the whole burst is transmitted. All frame transmissions are individually mapped to

certain code rate and modulation level based on the predicted received SINR. This

predicted SINR is based on some feedback from the base stations, as they have the

knowledge of all accepted & released calls, call routes and link path loss. A frame

received with SINRach less than SINRth,, is dropped by the receiver, and error

acknowledgement is sent to either the transmitter or base station. Based on the count of

these acknowledgements, a decision to re-route a call might be made in order to avoid

further degradation of throughput. Samples of various spectral efficiency coverage and

node throughput for each node are collected at the end of each frame time. The first 10%

of the collected statistics are rejected to minimize the initial bias, and to make sure that

steady state results are obtained.

43

Cont…

- Load Information on Network parameters, Nodes & BSs locations, Pathloss, Routing Tables. - Select Simulation time (T) in multiple of frame time, burst rate. - Generate No. of burst arrivals ‘N’ from Poisson distrib. for ‘T’ frames.

For K= 1: T

- Generate the size of each burst from exponential distribution. - Pick Source Nodes from uniform distribution.

“ Call Setup Procedure”

Call Setup Successful ?

N

Y

Increment Counters for Total Outage, Soft or Hard blocking

For J= 1: N(K)

- Increment 1 hop/ 2 hop/ 3 hop Counter correspondingly. - Update matrices for Active Calls, Data Transfer, Slot Occupancy, Interference levels, SINR etc.

N

Y

Are all Calls in Current Frame Checked for Admission?

(A)

44

Figure 3.1 Flow chart for main simulation program

Collect Samples of Spectral efficiency coverage & Node Throughput of all the nodes.

Update Adaptive Coding & Mod levels of all active calls for the next frame transmission.

- Update Data Transfer matrix - Identify the Calls on which Source Nodes & (or) Relays have completed their entire data transfer - Identify the Calls on which Data Retransmission is required

- Release all the Calls finished with data transmission - Update matrices for Active Calls, Data Transfer, Slot Occupancy, Interference levels, SINR etc.

Invoke “ Call Setup Procedure” to assign alternate routes to all those Calls requiring Data retransmission as identified above

- Increment 1 hop/ 2 hop/ 3 hop Counter depending upon the connection - Update matrices for Active Calls, Data Transfer, Slot Occupancy, Interference levels, SINR etc.

Decrement the 1 hop or 2 hop or 3 hop Counter depending upon the connection found for Calls requiring Data Retransmission

Is the Simulation Time Complete?

Y

N Next K (A)

- Save all collected Statistics - EXIT

45

Figure 3.2 Flow chart for call admission procedure

N

Y

Y N

Y

N

Y

Y

N Does 2-hop routing table exist between source node & BS(s)?

Node requesting service (From the main

program)

Choose the free matching time slot with highest

SINR >= SINRth

Set up the connection, and update all relevant

matrices.

Burst blocked due to unavailability of free slot (Hard blocking)

Does the free slot on the direct link with BS(s) has at least SINRth ?

Free slot available on Source Node

& BS(s) ?

Does 3-hop routing table exist between source node & BS(s)?

On this route; are there free matching slot(s) on each hop with SINRth?

Are all routes in the routing table

checked?

Pick the next best route from the routing table

Y

N

N

Source node denied service blocked due to total or partial contribution of the following reasons: - No MH route available. - MH routes present, but not available because of matching slot issue (Hard blocking). - MH routes with matching slots present but not available because of poor SINR (Soft blocking).

Return to Main Program

46

CHAPTER 4: SIMULATION RESULTS AND ANALYSIS

In this chapter, the simulation results for the system model discussed in the

previous chapter are presented and analyzed. Network performance results of both

multihop and traditional single-hop network in a TDMA-based fixed cellular architecture

are presented. These results are evaluated as a function of average generated node traffic

or offered node load. Network performance measures of interest considered are: outage,

net node throughput and spectral efficiency coverage. Sensitivity of these performance

measures to the number of available frequency channels in the system is evaluated, which

is one of the primary goals of this thesis.

The chapter is divided into three main sections based on the network performance

measure analyzed. Section 1 contains the results and detail analysis of outage in single-

hop and multihop network considered. The contribution of 2-hop and 3-hop connections

in reducing outage in multihop network are also presented. Section 2 contains results and

analysis of net node throughput, and how adaptive coding and modulation contributed to

it. These are elaborated using results of mean node spectral efficiencies and burst

readmission curves. Section 3 discusses the results of spectral efficiency coverage

potential offered by multihop network compared to a similar traditional single-hop

network. In each of these sections, first an overall performance comparison result of

single-hop and multihop network as a function of available frequency channel is

presented. Then detail analytical results are presented which shows the causes and

constraints behind each one of them.

47

It is important to remember that all these results and discussion are limited to two

main considerations. First, the single-hop network is pre-dominantly noise limited with

poor coverage. Second, multihopping is used only when necessary, based on the route

selection policy of minimum number of hops route first. Hence, the primary purpose of

introducing multihopping here is to minimize the outage not to maximize the node

throughput. High frequency reuse, and no separate relaying channels means high co-

channel interference as multi-hopping increases. Moreover, since the cell size is large

(with relatively large inter-node distances, noise and interference will dictate the SINR

and not the desired signal power. Therefore, if some higher average node throughput is

achieved, it will be an additional benefit.

Before starting discussion on the results, it will be appropriate to clarify the

terminology “Generated Traffic Per Node” used as the independent variable to evaluate

the results. It is assumed in the simulation that all the nodes are active and constantly

generating traffic. Generated traffic can also be referred to as “offered load”, and should

be treated as synonyms, wherever they appear in this document. As discussed in Chapter

3, the nature of this generated traffic is bursty. The rate of generation of these bursts is

directly proportional to the generated traffic per node. If one is interested in knowing the

aggregate generated network traffic or offered network load at a certain instant, he needs

to simply multiply the generated traffic per node by the number of nodes in the network.

The use of generated traffic per node informs the service provider of the user nodes’

performance as a function of the average offered load.

48

4.1 Outage Probability

In this study, outage is defined as the phenomenon that occurs when a requesting

node is denied service from the base station(s). Thus outage is an aggregate effect of two

major causes: poor coverage (inadequate SINR), and lack of frequency channel resources

(time slots).

Poor coverage means node(s) has inadequate SINR to establish a communication

link with the base station or other nodes. This type of outage is also referred to as “soft

blocking”. Inadequate SINR can be a combined effect of two or more factors such as,

large distance path loss (for nodes at the edge of the cell), deep shadowing, upper

constraint on transmit power, co-channel interference and noise power.

Lack of frequency channel resources (time slots) occurs, when a node requesting

service has adequate SINR to establish a link, but is denied services because of the

unavailability of time slots on the base station. This type of outage is also called “hard

blocking”.

4.1.1 Comparative Analysis of Outage in Single-hop and Multihop Network

Figure 4.1 shows a comparative analysis of outage in single-hop and multihop

networks with respect to number of available frequency channels. Single-hop network due

to the considered poor coverage, has consistently high outage (~38-40%) irrespective of

generated node traffic and the number of available frequency channels. This means that if

49

Figure 4.1 Average probability of outage in single-hop and multihop networks

with 2, 4 and 6 frequency channels

50

some nodes do not have single-hop coverage to the base station(s), then no matter how

much spectral resources (channels) are provided, they just cannot be served because of the

poor coverage. This poor coverage is the cost of low upfront infrastructure (limited

number of base stations). If frequency channels are few like in the case of 2 channels, then

at high node traffic levels, the impact of limited channels (time slots) exhaustion or hard

blocking also adds up, resulting in increased outage probability.

The strength of MH to provide high coverage is obvious from Figure 4.1. Even in

the absence of separate relaying channels, no frequency planning and fixed transmit

power; two to four orders of magnitude improvement (reduction) in outage probability is

achieved, depending upon the number of available frequency channel and average

generated traffic per node. As can be ascertained, if number of channels is increased to 4,

low outage probability can be obtained for higher node traffic levels. Increasing the

channels to 6, guarantees three to four order of magnitude improvement for light to

medium node traffic levels, and almost 60-70% reduced outage at high traffic levels.

This simply shows that, the more the number of frequency channels available, the

more profound are the improvement in outage from the use of multihopping. This is

because, when more channels are available, the source node and relay(s) have more

choices available to avoid high interference channels (time slots). Furthermore, using

switched beam directional antennas, nodes can choose viable relays to find a MH route to

the destination, thus ensuring high coverage and low outage probability.

51

4.1.2 Breakdown Analysis of Outage in Single-hop Network

The detailed outage analysis of single-hop network with respect to different

number of frequency channels is shown in Figure 4.2 to Figure 4.4. The total outage

phenomenon is broken into three major contributing factors:

§ Poor coverage (SINRach<SINRth) on all channels (and their time slots) of the base

stations, irrespective of time slots are free or not – (Soft blocking).

§ Unavailability of free time slots on the base stations – (Hard blocking).

§ Poor SINRach on the free time slots of the base stations – (Soft blocking).

Figure 4.2 shows the outage breakdown results for 2-channel single-hop network.

Consistent 38-40% outage due to initial poor coverage exists throughout, irrespective of

generated node traffic. Few channel resources (time slots) leads to hard blocking and

starts contributing to total outage at medium node traffic levels. This hard blocking keeps

growing as node traffic increases. This means an additional 2-15% outage over the range

of this traffic level. The total outage is further increased by inter-cell co-channel

interference due to frequency reuse of unity. Use of directional antennas minimizes this

effect to a great extent, but still another 2-5% outage result from it, at medium to high

traffic levels.

Figure 4.3 shows the outage breakdown analysis of single-hop network with 4

channels. With more frequency channels available, the impact of both unavailability of

time slot resources (hard blocking) and inter-cell interference (due to more choice of

interference avoidance) on outage probability almost vanishes over the entire range of

generated traffic except slightly at high traffic level.

52

Figure 4.2 Contribution of different factors in outage probability of

single-hop network with 2 channels

53

Figure 4.3 Contribution of different factors in outage probability of

single-hop network with 4 channels

54

Figure 4.4 shows the breakdown analysis of outage in single-hop network with 6

channels, where now the network has enough spectral resources (channels, time slots) to

accommodate the entire offered load from the nodes under the coverage region, and to

avoid any significant co-channel interference. Thus the outage is now entirely due to

nodes with initial poor coverage, and this is true over the entire range of offered load or

node traffic.

4.1.3 Breakdown Analysis of Outage in Multihop Network

For detailed outage analysis in multihop network, statistics are collected to show

contribution of the following three major factors in total outage.

§ Unavailability of free time slots on base stations – (Hard blocking).

§ Poor SINR on matching free slots on one or more hops of all available MH routes

between a source node and base stations –(Soft blocking).

§ Unavailability of matching free slots on one or more hops of all available MH routes

between a source node and base stations – (Hard blocking).

Since semi-connection oriented connection with digital relaying is considered here,

multihop connection requires larger service times (in terms of time slots occupancy) than

single-hop connection, provided the minimum SINR on any hop of the MH route is equal

to SINR on single-hop connection. This is because, if we can transfer some data us ing

single-hop in one time slot, then a 2-hop transmission will require the base station time

slot to be occupied for two frame times, one for the transmission of data from source node

55

Figure 4.4 Contribution of different factors in outage probability of

single-hop network with 6-channels

56

to relay (when BS slot is occupied but idle), and second for transmission from relay to BS

(when BS slot is occupied and active). Initially the slots on both hops have to be reserved,

until the data to be transmitted does not finishes on each transmitter on the route. As each

transmitter has finished sending all its data, it will release its resources (time slots).

Similarly a 3-hop connection will require a base station slot to be occupied for three frame

times compared to corresponding single-hop connection, and an m-hop connection will

require ‘m’ frame times.

At low traffic loads, this characteristic of multi-hopping does not matter much and

coverage enhancement of multi-hopping overrides this and gives reduced outage. But at

higher traffic loads, this issue becomes prominent, supplemented by higher co-channel

interference levels (both inter-cell and intra-cell), and consequently lower SINR levels on

the links (both because of frequency reuse and fixed Pt). This poor SINR further elongates

the duration of time slot occupancy as data transfer takes more time. All these factors lead

to higher outage.

This trend in MH network continues with the increase in network traffic load and

if frequency channels are few like in the case of 2 channels, even cross over occurs, where

single-hop and multi-hop outage converge. Further increase in node traffic leads to more

outage in MH networks, making single-hop networks a better choice, as shown in Figure

4.1. However as more frequency channels are provided, the outage reduction obtained

from multihopping is extended to higher traffic levels as clear from the curves of 4

channels and 6 channels in Figure 4.1.

57

The analysis of MH network presented in Figure 4.5 to Figure 4.7 verifies this

explanation. The major factor behind outage in MH network is the lack of channel

resources (time slots), and not poor SINR, irrespective of node traffic density. If

frequency channels are few like 2-channels, then as shown in Figure 4.5, this will start

showing up at lower traffic levels, and keep on growing as traffic load increases. The

contribution of poor SINR on outage is relatively much smaller throughout because of the

fact that every node has enough relays around it to choose from, such that high co-

channel interference can be avoided to achieve at least the SINR required for

communication.

As can be ascertained in Figure 4.5, the constraint of free matching time slots on a

MH route (discussed in chapter 3), is negligible. This means that even in the adverse

condition when only 2 channels are available, and a very low relay density is around, the

issue of matching free time slots does not matter. Of course, as more channels (time slots)

are available, and (or) relay density grows, chances are that this issue will become

insignificant.

Figure 4.6 shows the outage breakdown for MH network with 4 channels. It is

clear that as number of channel increases, the outage does not exist any more for light to

medium offered loads. The outage is shifted towards higher traffic levels, and again the

major contributing factor is resource limitation, for reasons already discussed. As

expected from the discussion in the previous paragraph, the issue of matching time slots

availability does not offer any impact on total outages.

58

Figure 4.5 Contribution of different factors in outage probability of

multihop network with 2 channels

59

Figure 4.6 Contribution of different factors in outage probability of

multihop network with 4 channels

60

As shown in Figure 4.7, further increasing the number of channels to 6 in MH

network, eliminated the outage over the extended range of generated node traffic levels,

except some at high traffic levels only, and that also primarily because of unavailability

of time slots.

The above multihop outage analysis reveals an interesting finding. Even with a

very low node density considered in this study (5.5 nodes/km2), the outage due to

unavailability of matching time slots on one or more hops of MH route is almost

negligible irrespective of the number of frequency channels and generated node traffic

load (ascertained in Figure 4.5 through Figure 4.7).

This simply means that there are enough relay nodes around every node, such that

a node with poor coverage can always find a viable relay to forward its traffic. Thus the

issue of matching time slots availability discussed in chapter 3 (System Model) does not

ascertain to be a constraining issue, at least with the minimum number of hops route first

assignment policy. This again is a proof of the immense potential present in

multihopping to provide high coverage.

The contribution of single-hop, 2 hop and 3 hop routes in enhancing the

connectivity is presented in this section. Figure 4.8 shows this contribution in multihop

network for 2-channel case. At low traffic levels, the nodes with no single-hop

connectivity are fully supported by 2-hop connections with sufficient SINR required for

connection setup, and 3-hop connections are never needed.

61

Figure 4.7 Contribution of different factors in outage probability of

multihop network with 6 channels

62

Figure 4.8 Contribution of m-hop connectivity in multihop network

with 2 channels

63

As the traffic load increases, more concurrent 2-hop connections are active. Since

no separate relaying channels are considered, this leads to higher inter-cell and intra-cell

co-channel interference. This means new connection requesting for service will find it

hard to get a 2-hop route with good SINR channels (time slots) on both hops, and they

will start using 3-hop connection with shorter links and hence higher SINR.

Conversely, more 3-hop routes mean more co-channel interference and for longer

durations (due to inherently longer service times associated with multihop connection

discussed before). This leads to a chain reaction of higher co-channel interference to the

extent that connectivity of MH network degrades beyond the similar single-hop network.

As the number of channels are increased to 4, chances of finding a 2-hop route

with viable SINR channels (time slots) on both hops is extended to medium traffic levels,

hence the need to switch to 3-hop connection is limited to high traffic levels, as shown in

Figure 4.9.

As shown in Figure 4.10, increasing the number of channels to 6, almost

eliminates the need for a 3-hop connection throughout the range of traffic levels

considered. This simply means that a 2-hop route with viable SINR channels is almost

always available.

64

Figure 4.9 Contribution of m-hop connectivity in multihop network

with 4 channels

65

Figure 4.10 Contribution of m-hop connectivity in multihop network

with 6 channels

66

4.2 Node Throughput

4.2.1 Comparative Analysis of Node Throughput in Single-hop and Multihop

Networks

Figure 4.11 shows the comparative analysis of average net node throughput of

single-hop and multihop networks with respect to an ideal network. In the ideal network,

there are no constraints such as frequency channels, SINR, transmit power etc. Hence all

the generated node traffic is supported and delivered to the destination. This means a

linear relationship of unity slope exist between average generated node traffic and

average net node throughput, as shown in Figure 4.11.

In SH network any traffic generated from poorly covered nodes is just not

supported, irrespective of the number of available frequency channels. Hence a slope of

approximately 0.62 (corresponding to SH coverage of 62% in this study) exists between

average generated node traffic and average net node throughput, for light to medium

traffic levels. The good SINR links are exploited using adaptive coding and modulation

based on the Table 1, specified in Chapter 3 (System Model). As traffic grows, the impact

of limited frequency channels and inter-cell co-channel interference comes into play

resulting in degradation of mean spectral efficiency (bps/Hz) of the nodes as shown in

Figure 4.12, and lower net node throughput shown in Figure 4.11. The use of directional

antennas on both the user nodes and base stations minimizes the interference to a great

extent, as observed from the results of outage in the previous section. Therefore, the

impact of limited frequency channels in throughput degradation is more prominent than

inter-cell interference.

67

Figure 4.11 Average net node throughput of single-hop and multihop

networks with 2, 4 and 6 frequency channels

68

Figure 4.12 Mean spectral efficiency of single-hop and multihop networks

with 2, 4 and 6 frequency channels

69

As the number of available frequency channels is increased to 4 in single-hop

network, not only is the degradation in node throughput shifted farther on the traffic

scale, but also it became less steep than the degradation in 2 channel case, as shown in

Figure 4.11. Similar less steep trend can be observed for the mean node spectral

efficiency for 4 channels single-hop network shown in Figure 4.12. A further increase in

the number of frequency channels to 6, ensures full throughput for all nodes under the

coverage, even at the highest offered load considered.

In MH network, full coverage and high SINR due to shorter links and fixed

transmit power lead to 100% node throughput for light to medium offered traffic levels as

shown in Figure 4.11. Higher SINR leads to higher adaptive coding and modulation

levels, resulting in much higher mean spectral efficiencies compared to the corresponding

single-hop counterpart, as can be ascertained in Figure 4.12. However, as generated

traffic level increase, more concurrent multihop routes exist in the network. This leads to

more frequency channel reuse (as no separate relaying channels are considered), and

longer channel occupancy. As a result, this introduces higher co-channel interference

levels (both inter-cell and intra-cell) and degradation in spectral efficiency as obvious

from Figure 4.12. If frequency channels are few like in the 2 channels multihop case, this

effect is more prominent; hence the resulting drop in spectral efficiency is quite steep,

with respect to increasing traffic. At low to medium traffic levels however, this drop in

spectral efficiency does not affect linearly the node throughput, because even after the

degradation in spectral efficiency, it is large enough to support the generated traffic, as

shown in Figure 4.11 and is still much superior to the corresponding SH network.

70

However, this superior performance is not realizable without a suitable re-transmission

and re-routing scheme. This is because; the high co-channel interference in MH network

can degrade some active connections to the extent of high frame outage probability.

A suitable ARQ scheme is needed to identify such high frame outage probability,

so that data can be retransmitted. But simply re-transmitting the data on the same route

will not solve the problem, because it will go through the same high frame outage due to

high co-channel interference on that route. This might lead to poor node throughput and

long transmission delays, which is not acceptable in real time applications and delay

sensitive services such as voice and video conferencing. Hence, the entire burst is

retransmitted from the source node after choosing a viable alternate route to the base

station. Figure 4.13 shows the probability of such re-transmission (and re-routing) for SH

and MH as the function of available frequency channels.

As can be ascertained, SH network rarely needs retransmission because of noise

limited nature of the system, irrespective of the number of available frequency channels.

Retransmission in MH network is a strong direct function of frequency channels. For MH

network with 2 channels, the probability of retransmission (and re-routing) grows steeply

with the increase in the offered node traffic, for obvious reason of high co-channel

interference. As the number of channels is increased to 4 in MH network, a significant

reduction in the retransmission can be ascertained, and full node throughput is extended

to medium-high traffic levels.

71

Further increase in traffic results in the degradation of node throughput for

reasons discussed above. With 6 channels, 100% node throughput is achieved over the

entire range of generate node traffic (and retransmission is rarely needed even at high

traffic levels as shown in Figure 4.11).

4.2.2 Contribution of Adaptive Coding and Modulation in Node Throughput of

Single-hop Network

The contribution of different adaptive coding and modulation schemes in the node

throughput of single-hop network with 2 channels is illustrated in Figure 4.14. Since the

SH network has only 62% coverage, 38% of the total data transmission (in terms of

frames) is just not supported due to poor SINR. Moreover at high loading levels, some

data traffic will be unsupported due to the unavailability of spectral resources (time slots).

This is because, both type of outages ultimately degrades the average node throughput.

Approximately 25% of the data transmission is based on minimum acceptable

ACM scheme of r:½-QPSK or 1 bps/Hz at light traffic, which simply means a

considerable percentage of nodes with single-hop coverage, can barely achieve the

minimum SINR level to support their transmissions. This is mainly because the SH

network considered is noise limited, and partly because of fixed (but independent)

shadowing. Therefore nodes experiencing deep shadowing will always experience weak

signal strength. This is to some extent been taken care of by using the policy of assigning

the best SINR channel (time slot) available.

72

Figure 4.13 Average probability of data retransmission in single-hop and

multihop networks with 2, 4 and 6 frequency channels

73

With the increase in average node traffic, intra-cell co-channel interference

(although weak) starts to degrade SINR on some of these r:½-QPSK links to the extent

that they cannot support the data transmission anymore, resulting in an increase in

unsupported transmissions and corresponding decrease in r:½-QPSK transmissions.

Furthermore, the unavailability of channels (time slots) at high traffic levels also

contributes to the unsupported transmission. A similar, but less steep trend can be

ascertained for r:¾-QPSK transmissions. Concerning, higher level modulation

transmissions, the degradation is not prominent because the SINR values are high enough

to be degraded appreciable by even the worst co-channel interference values arising from

the adjacent cells.

Figure 4.15 shows the contribution of adaptive coding and modulation in data

throughput of SH network with 4 channels. Only at high generated traffic levels, is a

slight increase in unsupported frames observed and a corresponding drop in r:½-QPSK

transmissions, while for all higher modulation level transmissions, the impact of

increasing network traffic is almost negligible.

Further increase in number of channels to 6 gives almost consistent performance

over the entire range of traffic level considered, as shown in Figure 4.16. This means that

enough channels (time slots) exist in the network so that nodes with coverage can always

avoid interference to achieve their desired throughput.

74

Figure 4.14 Contribution of different adaptive coding and modulation schemes

in node throughput of single-hop network with 2-channels

75

Figure 4.15 Contribution of different adaptive coding and modulation schemes

in node throughput of single-hop network with 4-channels

76

Figure 4.16 Contribution of different adaptive coding and modulation schemes

in node throughput of single-hop network with 6-channels

77

4.2.3 Contribution of Adaptive Coding and Modulation in Node Throughput of

Multihop Network

As can be ascertained from the results presented in Figure 4.17 for MH network

with 2 channels, not only are all data transmissions supported, but also significantly large

number of transmissions use high modulation levels. This is primarily because the

multihop routing tables are developed on the criterion (min{max(PLi)}), such that when a

MH route is chosen, it is the best among all available alternates. On top of that, the best

SINR free channels (time slots) are assigned. As the network traffic increases, more and

more MH concurrent transmissions result in large intra-cell and inter-cell co-channel

interference (because of no separate relaying channels), leading to a significant rise in

unsupported transmissions (frames).

This trend grows rapidly with increasing traffic, mainly because of the limited

number of channels to the point that it rises beyond that of a corresponding single-hop

network shown in Figure 4.14. This high number of unsupported transmission is not only

because of those transmissions which were barely supported previously at low coding and

modulation levels such as r:½-QPSK or r:¾-QPSK, but also from high modulation as can

be ascertained in Figure 4.17. This impact is much more pronounced at high traffic levels,

when transmissions on different code rates of 16-QAM and 64-QAM are almost

negligible.

Figure 4.18 shows the results for MH network with 4 channels. Here, since more

time slots are available, large interference time slots can be avoided to achieve higher

78

Figure 4.17 Contribution of different adaptive coding and modulation schemes

in node throughput of multihop network with 2-channels

79

Figure 4.18 Contribution of different adaptive coding and modulation schemes

in node throughput of multihop network with 4-channels

80

SINR. This leads to more frequent use of higher modulation levels of 16-QAM and 64-

QAM, and up to medium-high traffic levels. With further increase in traffic level, co-

channel interference becomes large enough to cause a substantial increase in unsupported

transmissions.

As shown in Figure 4.19, the increase in the number of channels to 6 enables data

transmissions to be carried out at different code rates of higher modulation levels.

Moreover, the use of high modulation levels are maintained over the entire range of

generated traffic load considered, as if co-channel interference has no impact. This

reflects the immense interference avoiding capability of MH network in general, and in

specific when directional antennas are used.

4.3 Spectral Efficiency Coverage

Before discussing spectral efficiency coverage, it would be appropriate to define

node coverage itself. In this study, node coverage is defined for single-hop and multihop

network as follows.

Single-hop Node Coverage: “Percentage of total number of nodes with 95% probability

of achieved signal to interference plus noise ratio (SINRach) greater than or equal to

targeted signal to interference plus noise ratio (SINRt) on any time slot (free or occupied)

of the base station(s)”.

81

Figure 4.19 Contribution of different adaptive coding and modulation schemes

in node throughput of multihop network with 6-channels

82

Multihop Node Coverage: “Percentage of total number of nodes with 95% probability of

SINRach greater than or equal to SINRt, on any time slot (free or occupied) of relay(s) and

base station”.

Spectral Efficiency Coverage: “Percentage of total number of nodes with coverage of

SINRt corresponding to a certain spectral efficiency”.

In this study we are mapping SINRach to adaptive coding and modulation,

therefore if a node has SINRach of 4.65-7.45 dB for 95% of the time, then based on

mapping in Table 1 (Chapter 3, System Model), this node has spectral efficiency

coverage of r:½-QPSK or 1 bps/hz. Similarly for SINRach of 14.02-15.0 dB for 95% of the

time, a node has spectral efficiency coverage of r:¾-16QAM or 3 bps/Hz, and so on.

SINRt can vary depending upon the service type and required quality of service.

By calculating SINR on both free and occupied slots, what we mean to do is to present

the potential in SH and MH networks to achieve certain SINR coverage. In other word, if

more frequency channel resources are provided, such coverage can be practically

guaranteed.

4.3.1 Spectral Efficiency Coverage in Single-hop Network

Figure 4.20 shows the potential of single-hop network to achieve a series of node

spectral efficiency coverage for 2-channel case. Approximately 62% have r:½-QPSK or 1

bps/Hz coverage. This spectral efficiency coverage is consistently available over the

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entire coverage of the traffic level considered in this study. Similarly 44% of the nodes

have r:¾-QPSK or 1.5bps/Hz coverage, and 32% have r:½-16QAM or 2 bps/Hz coverage

and so on.

It is worth noting that increasing generated traffic level is not affecting the

potential coverage except in the case of highest considered 64QAM or 6 bps/Hz

coverage. The reason is that the SH network considered is noise limited and directional

antennas are used, therefore even the highest co-channel interference arising from the

adjacent cells (frequency reuse=1) is not significant, and nodes can always find a time

slot (free or occupied) to achieve the desired SINR. Only in the case of 64QAM

coverage, which only 5% of the nodes have initially, this inter-cell co-channel

interference is large enough to slightly degrade the coverage to 2%.

If the number of channels are increased to 4, it can be ascertained that in Figure

4.21 that even the slight degradation in 64QAM coverage at high traffic levels does not

exist any more, simply because nodes not having the desired coverage previously, have

more time slots to choose from to achieve the required SINR.

Increasing the channel to 6 gives similar results (Figure 4.22), and no further

coverage improvement is achieved simply because, nodes outside the coverage region

just cannot attain it, irrespective of the number of frequency channels (or time slots)

provided.

84

Figure 4.20 Spectral efficiency coverage available in single-hop network

with 2-channels

85

Figure 4.21 Spectral efficiency coverage available in single-hop network

with 4-channels

86

Figure 4.22 Spectral efficiency coverage available in single-hop network

with 6-channels

87

4.3.2 Spectral Efficiency Coverage in Multihop Network

The strength of MH to improve coverage is reflected in the results below. Even in

the presence of high frequency reuse and no separate relaying channels to minimize

interference, MH offered substantial improvement in node coverage for all data rates.

Figure 4.23 shows the results for the 2-channel case. As can be ascertained, multihopping

leads to 100% node coverage of r:½-QPSK or 1bps/Hz over the entire range of traffic

level, as compared to only 62% in corresponding single-hop case (Figure 4.20).

In addition, the 100% node coverage is extended up to r:2/3-16QAM or 2.67

bps/Hz. This is followed by 98% node coverage of r:¾-16QAM or 3bps/Hz, and 95%

node coverage for r:7/8-16QAM or 3.5 bps/Hz, compared to only 25% and 23%

corresponding node coverage in similar single-hop network (Figure 4.20). This improved

coverage trend continues for higher spectral efficiency coverage too. However as traffic

grows, more and more concurrent MH routes exist in the network. This means aggressive

reuse of frequencies (time slots) as no separate relaying channels are considered. This

leads to both high inter-cell and intra-cell co-channel interference. On top of that,

multihopping has an inherent feature of occupying resources (channels or time slots) for

longer duration especially in case of digital relaying. This feature is a direct function of

the number of hops. Both these issues in MH links result in deterioration of SINR, and

therefore node coverage for high data rates starts degrading at medium to high traffic

levels. In case of r:7/8-64QAM, node coverage drops from 37% to 30%, while in

64QAM, it drops from 17% to 3%, almost the same as that of a similar SH network

(Figure 4.20).

88

Figure 4.23 Spectral efficiency coverage available in multihop network

with 2-channels

89

When the number of frequency channel is increased to 4, the node coverage of

r:7/8-64QAM improves to 36% and 64QAM to 12% at highest traffic level considered as

shown in Figure 4.24. This happens simply because now relays have more time slots

available and high interference can be avoided to ensure desired SINR on all hops.

Figure 4.25 shows that further increase in the number of frequency channels to 6,

leads to consistent node coverage over the entire range of traffic levels, for all considered

data rates.

90

Figure 4.24 Spectral efficiency coverage available in multihop network

with 4-channels

91

Figure 4.25 Spectral efficiency coverage available in multihop network

with 6-channels

92

CHAPTER 5: CONCLUSION AND FUTURE WORK

5.1 Thesis Summary

This research investigated and analyzed the performance gains, complexities and

constraints associated with multi-hopping in a TDMA based broadband fixed cellular

network, compared to a traditional cellular or single-hop network. The performance

metrics studied here are the outage probability, node throughout and spectral efficiency

coverage. Sensitivity of these performance metrics on the number of available frequency

channels is analyzed and discussed. A low user density network with few base stations is

considered, and both user terminal and base stations are equipped with directional,

switched beam antennas. Multi-hopping was implemented using the user node terminals,

hence no separate relaying entities or additional infrastructure were considered. Multi-

hopping capabilities were analyzed in a very hostile environment with around 60%

single-hop coverage no separate relaying channels aggressive frequency reuse and low

relay node density. This was chosen to ensure a fair comparison with traditional cellular

network on one hand, and to study the performance impacts of seamless extension of

multi-hopping feature to the existing widely deployed cellular network without incurring

any serious additional infrastructure cost.

Minimum number of hops selection policy is used with upper constraint of three

hops. Fixed power transmission is considered on all hops, with SINR mapping to

different adaptive coding and modulation schemes. Computer simulations were

93

developed for both single-hop and multihop networks to collect detailed statistics for in-

depth cause and effect analysis of all performance measures mentioned above, with

respect to increasing offered node traffic. Graphical results were presented with

discussion on each to gain deeper insight into the mechanisms controlling the system

performance of multi-hopping networks.

Even in the presence of such hostile channel conditions, promising results are

obtained to emphasize the high potential of multihopping in fixed cellular networks.

Results show that multihopping provide not only significant improvement (reduction) in

the outage probability, but also simultaneously yields high node throughput and spectral

efficiency coverage, compared with corresponding traditional single-hop cellular

networks. However, these performance gains are found to be strongly dependent on the

number of frequency channels in the system. In case of few channels, multihopping can

give initial performance benefits at very low node traffic, but as the offered load

increases, the performance degrades due to high co-channel interference, leading to a

significant drop in node throughput and large transmission delays. With increased

number of channels, superior multihop performance is guaranteed over the extensive

range offered node traffic. On the contrary, the single-hop network cannot benefit from

these increased channels, because nodes outside the coverage region will always

contribute to the outage and low average throughput irrespective of the number of

channels. The contributions of this study are summarized in the next section.

94

The results in general are very appealing for service providers looking to provide

affordable high data rate service to all users even in a low node density network.

Although user terminals might be a little more expensive, yet this additional cost can be

offset by multihopping capability of network scaling and low infrastructure cost. Proper

selection of cell sizes, based on node densities to ensure reasonable number of alternate

multihop routes, can be an important initial decision in a successfully feasible

deployment. Implementation of multihopping involves the complexity of routing and

overheads of control information exchange between nodes and BSs, but this is not a

critical issue here due to the fixed nature of user nodes. Although this study is performed

for the uplink, most of the findings are also applicable to downlink analysis. In fact,

downlink communication via multihopping will be more coordinated and well managed

since base stations can control network access more easily.

5.2 Thesis Contributions

This thesis has provided a series of interesting findings about multihop

implementation with no separate relaying channels, in TDMA based fixed cellular

networks with poor single-hop coverage. The thesis contributions are as follows.

1) Multihop performance benefits like low outage probability and high node

throughput are strongly dependent on the amount of available spectral resources

(number of available frequency channels or time slots) in the network.

95

2) A low relay density with good links in peer-to-peer relaying is enough to provide

high coverage enhancement expected from multihopping. In other words, relay

density is not a critical constraint (unless it is below realistic values) in providing

coverage

3) In noise limited single-hop networks, poor coverage is the primary performance

constraint, while in multihop networks, the main constraint is the spectral resources

(number of frequency channels).

4) If switched beam directional antennas are deployed at both user terminals and base

stations, then even in the absence of separate relaying channels, and in the presence

of high frequency reuse, multihopping can improve outage probability, node

throughput and high spectral efficiency coverage.

5) “Matching free time slots” bottleneck in low relay density TDMA based multihop

network, as discussed in chapter 2 is not found to be a critical issue, irrespective of

the number of available frequency channels.

6) It is found that, if switched beam directional antennas are used, multihopping has

the potential of converting an interference limited system into an almost noise

limited system, by avoiding high interference channels (time slots) and bad relay

links.

96

7) In the absence of separate relaying channels and power control, the defensive

approach of using multihopping only when necessary, not only provides outage

gains but also automatically yields high node throughput.

8) If “minimum number of hop routes first” route selection policy is used, then 2 hop

routes are sufficient if high number of frequency channels are available, even if

relay density is low.

9) High spectral efficiency coverage in multihop network is a direct function of the

relay node density.

10) Fixed transmit power is acceptable in multihopping at low traffic densities, but

leads to high co-channel interference and serious performance degradation at

medium-high offered traffic levels.

11) A good transmission scheduling and load balancing algorithm is needed to extract

high node throughput and low transmission delays from multihopping in a highly

aggressive frequency reuse environment with few channels.

97

5.3 Receiver Complexity Issues:

Some receiver issues associated with the system model are discussed

below:

§ Since we are using switched beam directional antennas on the nodes as well as the

base stations, during a particular time slot, a node would be communicating with

another node or base station using a specific channel. If more than one channel is

available, then a corresponding number of switched beams will be required. If

TDD is used, then slot reservation has to be done for uplink and downlink

communication. TDD implementation is cost effective, as no extra hardware is

required, however there are associated delay and scheduling overheads. FDD can

be implemented by using a duplex switch for each beam, moreover sufficient

spacing between the carriers should be considered to avoid high adjacent channel

interference.

§ Multiple frequency channels require additional receiver hardware, with one RF

chain for each channel.

§ Buffered transmission with independent ACM selection on each hop requires a

large buffer space on each node. Receiver should be smart enough to manage the

data arriving from various users on different channels, process them, and transmit

them to the desired locations. Therefore the buffer size and hence cost will the

increase with increase in the offered load, and number of channels.

98

§ Instantaneous transmit power of each relayer node will increase as the relayer

load and number of channels increases. This is so because, at high relaying load, a

relayer will be simultaneously transmitting power on multiple channels, hence

high rating power amplifiers will be needed. Although energy availability is not

the constraint due to stationary positioning of the nodes, the receiver will be

complex and expensive.

5.4 Proposed Future Research

Based on the findings and issues derived from this thesis, there seems to be great

room for further investigations in this area. Some of possible relevant studies that can

further enhance the understanding of fixed multihop cellular networks could be:

§ Sensitivity analysis of the MH network performance on the number of available

frequency channels with power control.

§ Performance evaluation of MH network with different route selection schemes like

max{min(SINRi)}, QoS based, etc, as a function of available frequency channels, with

and without power control.

§ Sensitivity analysis of the MH network performance on the number of available

frequency channels without intermediate relay buffering.

99

§ Generally multihop implementation requires large control information exchange

among nodes and base stations (which is an overhead); therefore investigation should

be done to evaluate performance of MH Networks with local and global spectral

resource utilization policies. Performance sensitivity against relay density and number

of frequency channels can be analyzed.

§ Performance evaluation of the fixed MH Network, using indoor user terminals with

omni-directional antennas (no relaying capability), and fixed relay units with

directional antennas pointed to the base stations. Performance sensitivity on the relay

node density and different frequency reuse factor can be investigated.

§ Evaluation of different scheduling algorithms for time slots allocation to analyze their

impact on SINR and transmission delays in fixed MH networks.

§ Impact of diversity (space and macro) on the performance of fixed MH Networks.

§ Performance evaluation of fixed MH networks with CDMA /OFDMA.

§ Performance evaluation of multihopping in fixed cellular packet switched networks.

100

REFERENCES

[1] Y.-D. Lin and Y.-C. Hsu, “Multi-hop cellular: A new architecture for wireless

communication”, IEEE INFOCOM 2000, pp. 1273-1282.

[2] R. Ananthapadmanabha, B.S. Manoj, and C. S. Murthy, “Multi-hop cellular

networks: The architecture and routing protocols”, IEEE PIMRC 2001, vol. 2, pp.

G78-G82.

[3] T. Fowler, “Mesh performance in finite spectrum” v1.0.doc, white paper, Radiant

Broadband Wireless Access Network, 2001. www.radiantnetworks.com

[4] V. Sreng, H. Yanikomeroglu, and D. Falconer, “Coverage enhancement through

two-hop relaying in cellular radio systems”, IEEE WCNC 2002, vol.2. pp. 881-

885.

[5] W. Zirwas, M. Lampe, H. Li, M. Lott, M. Weckerle, and E. Schulz, “Multihop

communications in future mobile radio networks”, IEEE PIMRC 2002, vol. 1, pp.

54-58.

[6] T.S. Rappaport, Wireless Communication: Principles & Practices, Chapter 3,

Prentice Hall PTR, 1996.

[7] G. Caire, G. Taricco, and E. Biglieri, “Bit- interleaved coded modulation”, IEEE

Trans. on Info. Theory, May 1998, vol. 44, no. 33, pp. 927-946.

[8] IEEE 802.16, Air Interface Standard Draft for Fixed Wireless Access in 2-11 GHz,

Ref . No. IEEE P802.16a/D4-2002.

[9] J. Proakis, Digital Communications, McGraw-Hill, New York, 3rd Edition, 1995.

[10] J. Laneman and G. Wornell, “Energy efficient antenna sharing and relaying for

wireless network”, IEEE WCNC 2000, vol. 1, pp. 7-12

[11] A. Sendonaris, E. Erkip, and B. Aazhang, “User cooperative diversity – part I:

system description”, IEEE Transactions on Communications, 2003, vol. 51, issue

11, pp. 1927-1938.

[12] T. Harold and A. Nix, “Intelligent relaying for future personal communications

systems”, IEE Colloquium on Capacity and Range Enhancement Technique for

Third Generation Mobile Communications and Beyond, 2000, pp. 9/1-9/5.

101

[13] J. Boyer, D. Falconer, and H. Yanikomeroglu, “A theoretical characterization of

multihop wireless communication channels without diversity”, IEEE PIMRC,

2001, vol. 2, pp. E116-E120.

[14] J. Boyer, D. Falconer, and H. Yanikomeroglu, “A theoretical characterization of

multihop wireless communication channels with diversity”, IEEE Globecom,

2001, vol. 2, pp. 841-845.

[15] C. Qiao, H. Wu, and O. Tonguz, “Load balancing via relay in next generation

wireless systems”, Proceedings of Mobile and Adhoc Networking and Computing

Conference, 2000, pp. 149-150.

[16] B. Sklar, Digital Communications: Fundamentals and Applications, Chapter 6, 2nd

Edition Prentice Hall PTR, 1996.

[17] H. Yanikomeroglu, “Fixed and mobile relaying technologies for cellular

networks”, Second Workshop on Applications and Services in Wireless Networks,

ASWN, 2002, pp. 75-81, July 2002

[18] H. Yanikomeroglu, D. Falconer, and V. Sreng, “Coverage enhancement through

two hop peer-to-peer relaying in cellular radio systems”, World Wireless Research

Forum (WWRF), meeting No. 7, 2002.

[19] V. Sreng, H. Yanikomeroglu, and D. Falconer, “Peer selection strategies in peer-

to-peer relaying in cellular networks”, IEEE VTC Fall 2003

[20] E.H. Drucker, “Development and application of a cellular repeater”, IEEE VTC

1988, pp. 321-325.

[21] V.S. Kaunismaa, “On frequency radio (OFR) repeater as fade filler”, IEEE VTC

Spring 1989, pp. 528-531.

[22] V. Erceg et. al, “ Channel models for fixed wireless applications”, contribution

Ref: IEEE 802.16.3c-01/29r4, September 2001.

[23] S. Hares, H. Yanikomeroglu, and B. Hashem, “Multihop relaying with diversity in

peer-to-peer networks”, IEEE, VTC Fall 2003, accepted, unpublished yet.

[24] A. Sendonaris, E. Erkip, and B. Aazhang, “User cooperative diversity – part II:

implementation aspects and performance analysis”, IEEE Transactions on

Communications, 2003, vol. 51, issue 11, pp. 1939-1948.

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